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Quorum-sensing dysbiotic shifts in the HIV-infected oral metabiome.

Brown RE, Ghannoum MA, Mukherjee PK, Gillevet PM, Sikaroodi M - PLoS ONE (2015)

Bottom Line: We implemented a Systems Biology approach using Correlation Difference Probability Network (CDPN) analysis to provide insights into the statistically significant functional differences between HIV-infected patients and uninfected individuals.CDPN highlights the taxa-metabolite-taxa differences between the cohorts that frequently capture quorum-sensing modifications that reflect communication disruptions in the dysbiotic HIV cohort.The results also highlight the significant role of cyclic mono and dipeptides as quorum-sensing (QS) mediators between oral bacteria and fungal genus.

View Article: PubMed Central - PubMed

Affiliation: School of Systems Biology, George Mason University, Prince William County, Fairfax, VA, United States of America.

ABSTRACT
We implemented a Systems Biology approach using Correlation Difference Probability Network (CDPN) analysis to provide insights into the statistically significant functional differences between HIV-infected patients and uninfected individuals. The analysis correlates bacterial microbiome ("bacteriome"), fungal microbiome ("mycobiome"), and metabolome data to model the underlying biological processes comprising the Human Oral Metabiome. CDPN highlights the taxa-metabolite-taxa differences between the cohorts that frequently capture quorum-sensing modifications that reflect communication disruptions in the dysbiotic HIV cohort. The results also highlight the significant role of cyclic mono and dipeptides as quorum-sensing (QS) mediators between oral bacteria and fungal genus. The developed CDPN approach allowed us to model the interactions of taxa and key metabolites, and hypothesize their possible contribution to the etiology of Oral Candidiasis (OC).

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Related in: MedlinePlus

MBF HIV cohort significant correlations (rho >0.6 or rho <-0.6).A blue edge depicts a positive correlation; a red edge depicts a negative correlation. The correlation value is listed on the edge. The node shape defines the type; diamond is metabolite, parallelogram is bacteria, and circle for fungi. The location of the node, and the link length, and orientation, is not significant.
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pone.0123880.g003: MBF HIV cohort significant correlations (rho >0.6 or rho <-0.6).A blue edge depicts a positive correlation; a red edge depicts a negative correlation. The correlation value is listed on the edge. The node shape defines the type; diamond is metabolite, parallelogram is bacteria, and circle for fungi. The location of the node, and the link length, and orientation, is not significant.

Mentions: We present the significant correlations for the MBF Control cohort in Fig 2 and the MBF HIV disease cohort in Fig 3. Only 21 of the significant correlations with (rho <-0.6 or rho >0.6) in the MBF Control group overlapped with the MBF HIV significant correlation group. There were 452 significant Control correlations involving a bacteria or fungus with another feature of the possible 17,020 (0.8%). The significant oral metabiome correlations totaled 288 of the possible 17,205 (1.2%). S3 Table is the feature1 (node)—feature2 (node) pair listing with key metadata corresponding to correlation (edge) network relationships in the combined Figs 2 and 3.


Quorum-sensing dysbiotic shifts in the HIV-infected oral metabiome.

Brown RE, Ghannoum MA, Mukherjee PK, Gillevet PM, Sikaroodi M - PLoS ONE (2015)

MBF HIV cohort significant correlations (rho >0.6 or rho <-0.6).A blue edge depicts a positive correlation; a red edge depicts a negative correlation. The correlation value is listed on the edge. The node shape defines the type; diamond is metabolite, parallelogram is bacteria, and circle for fungi. The location of the node, and the link length, and orientation, is not significant.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4401692&req=5

pone.0123880.g003: MBF HIV cohort significant correlations (rho >0.6 or rho <-0.6).A blue edge depicts a positive correlation; a red edge depicts a negative correlation. The correlation value is listed on the edge. The node shape defines the type; diamond is metabolite, parallelogram is bacteria, and circle for fungi. The location of the node, and the link length, and orientation, is not significant.
Mentions: We present the significant correlations for the MBF Control cohort in Fig 2 and the MBF HIV disease cohort in Fig 3. Only 21 of the significant correlations with (rho <-0.6 or rho >0.6) in the MBF Control group overlapped with the MBF HIV significant correlation group. There were 452 significant Control correlations involving a bacteria or fungus with another feature of the possible 17,020 (0.8%). The significant oral metabiome correlations totaled 288 of the possible 17,205 (1.2%). S3 Table is the feature1 (node)—feature2 (node) pair listing with key metadata corresponding to correlation (edge) network relationships in the combined Figs 2 and 3.

Bottom Line: We implemented a Systems Biology approach using Correlation Difference Probability Network (CDPN) analysis to provide insights into the statistically significant functional differences between HIV-infected patients and uninfected individuals.CDPN highlights the taxa-metabolite-taxa differences between the cohorts that frequently capture quorum-sensing modifications that reflect communication disruptions in the dysbiotic HIV cohort.The results also highlight the significant role of cyclic mono and dipeptides as quorum-sensing (QS) mediators between oral bacteria and fungal genus.

View Article: PubMed Central - PubMed

Affiliation: School of Systems Biology, George Mason University, Prince William County, Fairfax, VA, United States of America.

ABSTRACT
We implemented a Systems Biology approach using Correlation Difference Probability Network (CDPN) analysis to provide insights into the statistically significant functional differences between HIV-infected patients and uninfected individuals. The analysis correlates bacterial microbiome ("bacteriome"), fungal microbiome ("mycobiome"), and metabolome data to model the underlying biological processes comprising the Human Oral Metabiome. CDPN highlights the taxa-metabolite-taxa differences between the cohorts that frequently capture quorum-sensing modifications that reflect communication disruptions in the dysbiotic HIV cohort. The results also highlight the significant role of cyclic mono and dipeptides as quorum-sensing (QS) mediators between oral bacteria and fungal genus. The developed CDPN approach allowed us to model the interactions of taxa and key metabolites, and hypothesize their possible contribution to the etiology of Oral Candidiasis (OC).

Show MeSH
Related in: MedlinePlus